Comparison of outcome of patients with CLL who are referred or nonreferred to a specialized <scp>CLL</scp> clinic: a Canadian population‐based study
Bibliographic record
Abstract
Chronic lymphocytic leukemia and small lymphocytic lymphoma (CLL/SLL) patients in Manitoba are either referred to the CLL Clinic at CancerCare Manitoba (CCMB) or are followed by other hematologists and general practitioners. However, it has been unclear whether referral to the CLL clinic influences patient outcome. Overall survival (OS) was assessed for all CLL/SLL patients diagnosed in Manitoba between 2007 and 2011. Of 555 patients, 281 (51%) were referred to the CLL clinic. Patients seen in this clinic had a twofold increased OS compared to patients who were managed by other hematologists and general practitioners (HR 2.375, P 0.0002) when adjusted for age, gender, presence of pre- or post-CLL cancer, treatment and urban/rural location. In the nonreferred population there was a striking correlation between advancing age and decreasing OS. However, this correlation was almost eliminated in the referred population who were more likely to receive chemotherapy. Patients referred and seen in the CLL clinic have an improved OS compared to nonreferred patients and this appears to be primarily related to improved OS in the elderly. Possible explanations for this finding are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".